A Mechanism for Cytoplasmic Streaming: Kinesin-Driven Alignment of Microtubules and Fast Fluid Flows.

The transport of cytoplasmic components can be profoundly affected by hydrodynamics. Cytoplasmic streaming in Drosophila oocytes offers a striking example. Forces on fluid from kinesin-1 are initially directed by a disordered meshwork of microtubules, generating minor slow cytoplasmic flows. Subsequently, to mix incoming nurse cell cytoplasm with ooplasm, a subcortical layer of microtubules forms parallel arrays that support long-range, fast flows. To analyze the streaming mechanism, we combined observations of microtubule and organelle motions with detailed mathematical modeling. In the fast state, microtubules tethered to the cortex form a thin subcortical layer and undergo correlated sinusoidal bending. Organelles moving in flows along the arrays show velocities that are slow near the cortex and fast on the inward side of the subcortical microtubule layer. Starting with fundamental physical principles suggested by qualitative hypotheses, and with published values for microtubule stiffness, kinesin velocity, and cytoplasmic viscosity, we developed a quantitative coupled hydrodynamic model for streaming. The fully detailed mathematical model and its simulations identify key variables that can shift the system between disordered (slow) and ordered (fast) states. Measurements of array curvature, wave period, and the effects of diminished kinesin velocity on flow rates, as well as prior observations on f-actin perturbation, support the model. This establishes a concrete mechanistic framework for the ooplasmic streaming process. The self-organizing fast phase is a result of viscous drag on kinesin-driven cargoes that mediates equal and opposite forces on cytoplasmic fluid and on microtubules whose minus ends are tethered to the cortex. Fluid moves toward plus ends and microtubules are forced backward toward their minus ends, resulting in buckling. Under certain conditions, the buckling microtubules self-organize into parallel bending arrays, guiding varying directions for fast plus-end directed fluid flows that facilitate mixing in a low Reynolds number regime.

3D single cell scale anatomical map of sex-dependent variability of the rat intrinsic cardiac nervous system.

We developed and analyzed a single cell scale anatomical map of the rat intrinsic cardiac nervous system (ICNS) across four male and three female hearts. We find the ICNS has a reliable structural organizational plan across individuals that provide the foundation for further analyses of the ICNS in cardiac function and disease. The distribution of the ICNS was evaluated by 3D visualization and data-driven clustering. The pattern, distribution, and clustering of ICNS neurons across all male and female rat hearts is highly conserved, demonstrating a coherent organizational plan where distinct clusters of neurons are consistently localized. Female hearts had fewer neurons, lower packing density, and slightly reduced distribution, but with identical localization. We registered the anatomical data from each heart to a geometric scaffold, normalizing their 3D coordinates for standardization of common anatomical planes and providing a path where multiple experimental results and data types can be integrated and compared.

The coming paradigm shift: A transition from manual to automated microscopy.

The field of pathology has used light microscopy (LM) extensively since the mid-19(th) century for examination of histological tissue preparations. This technology has remained the foremost tool in use by pathologists even as other fields have undergone a great change in recent years through new technologies. However, as new microscopy techniques are perfected and made available, this reliance on the standard LM will likely begin to change. Advanced imaging involving both diffraction-limited and subdiffraction techniques are bringing nondestructive, high-resolution, molecular-level imaging to pathology. Some of these technologies can produce three-dimensional (3D) datasets from sampled tissues. In addition, block-face/tissue-sectioning techniques are already providing automated, large-scale 3D datasets of whole specimens. These datasets allow pathologists to see an entire sample with all of its spatial information intact, and furthermore allow image analysis such as detection, segmentation, and classification, which are impossible in standard LM. It is likely that these technologies herald a major paradigm shift in the field of pathology.